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Automatic Text Summarization (English/Arabic).

Home Page: http://sumrized.com/

License: GNU General Public License v3.0

Python 49.34% Jupyter Notebook 50.66%
nlp-machine-learning text-summarization arabic-nlp

sumrized's Introduction

Sumrized

Arabic Text Summarization

Starting Project

  • Make sure you have installed pip (Python 3)

    sudo apt-get install python3-pip
    
  • Make sure you have NLTK (Natural Language Tool Kit) installed (Python 3)

    sudo pip install -U nltk
    

Project content

.  
├── docs                    <- All documentation about project
│   ├── reports             <- Reports for current project advancement 
│   ├── references          <- All references papers, links related to this project goes here   
│   └── sphinx              <- Automaticaly genereated API documentation form stringdocs in code
│
├── lib                     <- All project's source code goes here
│   ├── data-generation     <- Code for data generation if needed 
│   └── preprocessing       <- Code for data preprocessing 
│ 
├── models                  <- Contains code to train, test and run models 
│   ├── dumps               <- trained models file
│   └── scripts             <- script to run models 
│ 
├── Readme.md               <- Contains current project info
├── requirements.txt        <- Packages and modules needed for the current project to run
└── tests                   <- Unit test for the code in lib/ 
    └── lib  
        ├── analysis  
        ├── data-generation   
        └── preprocessing
   

Guide lines

Data

  • Symlink to your Raw data

        user@host:/my/awesome/project$ ln -s /path/to/your/raw/data . 
    
  • Data location must follow this structure:

data  
├── raw             <- Raw data
├── temp            <- transformed data stored temporarily if needed 
└── preprocessed    <- preprocessed data to run in a model

Data is immutable

  • Treat the data/raw (and its format) as immutable. Don't ever edit your raw data, especially not manually, and especially not in Excel.
  • Don't overwrite your raw data. Don't save multiple versions of the raw data.
  • The code you write should move the raw data through a pipeline to your final analysis.
  • You shouldn't have to run all of the steps every time you want to make a new figure, but anyone should be able to reproduce the final products with only the code in lib/ and the data in data/raw.

sumrized's People

Contributors

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sumrized's Issues

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